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August 13, 2026
‘Working with AI Solves a Wide Range of Engineering Problems
Artificial intelligence is a working tool based on a balanced combination of algorithms and engineering. Experts and doctoral students from the HSE Moscow Institute of Electronics and Mathematics explain how AI technologies can improve an application, device, or system, and what engineering tasks are solved in the process.
August 12, 2026
‘I Would Like My Research to Help Make the World a Calmer and Better Place
Whatever task Saraa Ali, Junior Research Fellow at the Laboratory of Methods for Big Data Analysis (LAMBDA) of the AI and Digital Science Institute (HSE Faculty of Computer Science), is working on, she thinks about how it can benefit people. She told the Young Scientists of HSE University project about her large family, diagnosing three-phase motors, and her dream of building a children’s home in her native country.
August 11, 2026
‘The Peak of Stupidity and ‘The Valley of Despair: HSE Economists Propose an Explanation for the Dunning–Kruger Effect
The Dunning–Kruger effect, which describes a sharp surge in self-confidence among beginners followed by an equally rapid decline as they gain experience, can be explained by the nature of the learning process and the acquisition of new knowledge. This conclusion was reached by Andrey Vorchik of the HSE Faculty of Economic Sciences together with independent researcher Murat Mamyshev. They developed a mathematical model of learning and demonstrated how subjective confidence is formed and changes as knowledge accumulates, as well as how teachers can reduce the ‘valley of despair’ experienced by learners.

 

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Discourse relations and evaluation.

Corpora. 2016. P. 169–190.
Trnavac Radoslava, Das D., Taboada M.

n this paper, we examine the role of discourse relations (relations between propositions) in the interpretation of evaluative or opinion words. Through a combination of Rhetorical Structure Theory (or RST; Mann and Thompson, 1988) and Appraisal Theory (Martin and White, 2005), we analyse how different discourse relations modify the evaluative content of opinion words, and what impact the nucleus–satellite structure in RST has on the evaluation. We conduct a corpus study, examining and annotating over 3,000 evaluative words in fifty movie reviews in the SFU Review Corpus (Taboada, 2008) with respect to five parameters: word category (noun, verb, adjective or adverb), prior polarity (positive, negative or neutral), RST structure (both nucleus–satellite status and relation type) and change of polarity as a result of being part of a discourse relation (Intensify, Downtone, Reversal or No Change). Results show that relations such as Concession, Elaboration, Evaluation, Evidence and Restatement most frequently intensify the polarity of opinion words, although the majority of evaluative words do not undergo changes in their polarity related to the type of relation that they are a part of. We also find that most opinion words (about 70 percent) are positioned in the nucleus, confirming a hypothesis based on the literature that nuclei are the most important units when extracting opinion automatically.

Research target: Philology and Linguistics
Language: English
DOI
Text on another site
Keywords: evaluationpolaritydiscourse relationsAppraisalRhetorical Structure Theory
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